Schubert, P, Lund, M, Strom, L, Eklundh, L (2010). Impact of nutrients on peatland GPP estimations using MODIS time series data. REMOTE SENSING OF ENVIRONMENT, 114(10), 2137-2145.
Time series of satellite sensor-derived data can be used in the light use efficiency (LUE) model for gross primary productivity (GPP). The LUE model and a closely related linear regression model were studied at an ombrotrophic peatland in southern Sweden. Eddy covariance and chamber GPP, incoming and reflected photosynthetic photon flux density (PPFD), field-measured spectral reflectance, and data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used in this study. The chamber and spectral reflectance measurements were made on four experimental treatments: unfertilized control (Ctrl). nitrogen fertilized (N), phosphorus fertilized (P), and nitrogen plus phosphorus fertilized (NP). For Ctrl, a strong linear relationship was found between GPP and the photosynthetically active radiation absorbed by vegetation (APAR) (R-2=0.90). The slope coefficient (epsilon(s), where s stands for slope) for the linear relationship between seasonal time series of GPP and the product of the normalized difference vegetation index (NDVI) and PPFD was used as a proxy for the light use efficiency factor (epsilon). There were differences in epsilon(s) depending on the treatments with a significant effect for N compared to Ctrl (ANOVA: p = 0.042, Tukey's: p <= 0.05). Also. epsilon(s) was linearly related to the cover degree of vascular plants (R-2= 0.66). As a sensitivity test, the regression coefficients (epsilon(s) and intercept) for each treatment were used to model time series of 16-day GPP from the product of MODIS NDVI and PPFD. Seasonal averages of GPP were calculated for 2005, 2006. and 2007, which resulted in up to 19% higher average GPP for the fertilization treatments compared to Ctrl. The main conclusion is that the LUE model and the regression model can be applied in peatlands but also that temporal and spatial changes in epsilon or the regression coefficients should be considered. (C) 2010 Elsevier Inc. All rights reserved.